机器学习支持下的京津冀地区农田生态系统服务交互作用及时空演变分析

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关键词：农田；生态系统服务；机器学习算法；权衡/协同；生态系统服务簇中图分类号：TP181;X171.1 文献标志码：A 文章编号：1672-2043（2025）11-2820-15 doi：10.11654/jaes.2025-0459

Abstract：Thepurposeofthisstudywastorvealtheinteractionbetweenfarmlandecosystemservicesandteirspatiotemporalevolution characteristics，soastosupporttheimprovementofregionalcultivatedlandresourcemanagementandcosstemsustainabilityIntis study，thefalandosystesintheeijing-anjnHebeiregionwerestudiedio0，2015and23，andfourfarmlandoste servicefunctions，amelyfoodsuppyarbonstrage，soilconserationndwaterproductionservics，wereessedsedte InVESTodelandthegrainyieldestimationmodel，andthetrade-offs/snergieswerequantifiedusingSpearman’scoelationand geographicallyweighedegessonodelsndteundsoffrlandosstsersereidentifdwiththsupportofclearningalgoritmsupportidentiedbundlesoffarmlandecosystemservices.Teresultsshowedthatthesignificantspatialadteporal variationsinfarmlandecosystemservicesocuredintheBeijing-Tanjin-HebeiregionfromOotoO23inichwaterroducing servicesadfoodproductionapacityeregaduallyancedspeiallineuthndoastalgios，ndsoiletiod carbonstorageshowedfluctuatingchanges.Waterproductionservicessyergiedwithsoilconsevatioandfoodsuplyservicesineased， whilecarbonstorageandotherserviceschangedrepeatedlybetweensynergiesandtrade-offs.Thefarmlandecosystemservicebundles showedsignificantevoution，witteexpasnoffoddomnantandateproducingfodomplexudes，ndthsikagol fod-complexandcarbonstorage-dominantbundles.Thisstudydevelopedanevaluationframeworkthatintegratestheidentificationof interactionsamongfarmlandosytmserviceswithspatialusteringanalyss.Tersultsdemonstratethatheframeworkcanfectively capture the trade-offs and synergies among services as well as their spatiotemporal evolution patterns.

KeyWords：farmland; ecosystem services; machine learning algorithms; trade-offs/synergies; ecosystem servicebundles

农田生态系统是陆地生态系统的重要组成部分，在维护生态结构完整性和生态安全方面具有关键作用。（剩余18440字）